Using Deep Neural Networks to make YouTube Recommendations

The recommendation system they designed has two stages. Candidate generation network takes events from users YouTube history. This can only provide broad personalization using collaborative filtering. These users are then compared by identifiers such as the number of videos watched, demographic information and search query tokens. The ranking network operates a little differently.